Evidence map›Paper›PMID 25886976›Full record

ArticleBMC medical research methodology2015

Strategies for monitoring and evaluation of resource-limited national antiretroviral therapy programs: the two-phase design.

Sebastien Haneuse, Bethany Hedt-Gauthier, Frank Chimbwandira, Simon Makombe, Lyson Tenthani, Andreas Jahn

Abstract read
In one paragraph

Article in BMC medical research methodology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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  3. Augmented pseudo-likelihood estimation for two-phase studies.Statistical methods in medical research · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Sebastien HaneuseDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. shaneuse@hsph.harvard.edu.
Bethany Hedt-GauthierDepartment of Global Health and Social Medicine, Harvard Medical School, Boston, MA, USA. bethhedt@gmail.com.
Frank ChimbwandiraDepartment for HIV and AIDS, Ministry of Health, Lilongwe, Malawi. frankchimbwandira@gmail.com.
Simon MakombeDepartment for HIV and AIDS, Ministry of Health, Lilongwe, Malawi. simond.makombe@yahoo.com.
Lyson TenthaniDepartment for HIV and AIDS, Ministry of Health, Lilongwe, Malawi. ltenthani@gmail.com.
Andreas JahnDepartment for HIV and AIDS, Ministry of Health, Lilongwe, Malawi. drandreasjahn@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn resource-limited settings, monitoring and evaluation (M&E) of antiretroviral treatment (ART) programs often relies on aggregated facility-level data. Such data are limited, however, because of the potential for ecological bias, although collecting detailed patient-level data is often prohibitively expensive. To resolve this dilemma, we propose the use of the two-phase design. Specifically, when the outcome of interest is binary, the two-phase design provides a framework within which researchers can resolve ecological bias through the collection of patient-level data on a sub-sample of individuals while making use of the routinely collected aggregated data to obtain potentially substantial efficiency gains.

methodsBetween 2005-2007, the Malawian Ministry of Health conducted a one-time cross-sectional survey of 82,887 patients registered at 189 ART clinics. Using these patient data, an aggregated dataset is constructed to mimic the type of data that it routinely available. A hypothetical study of risk factors for patient outcomes at 6 months post-registration is considered. Analyses are conducted based on: (i) complete patient-level data; (ii) aggregated data; (iii) a hypothetical case-control study; (iv) a hypothetical two-phase study stratified on clinic type; and, (v) a hypothetical two-phase study stratified on clinic type and registration year. A simulation study is conducted to compare statistical power to detect an interaction between clinic type and year of registration across the designs.

resultsAnalyses and conclusions based solely on aggregated data may suffer from ecological bias. Collecting and analyzing patient data using either a case-control or two-phase design resolves ecological bias to provide valid conclusions. To detect the interaction between clinic type and year of registration, the case-control design would require a prohibitively large sample size. In contrast, a two-phase design that stratifies on clinic and year of registration achieves greater than 85% power with as few as 1,000 patient samples.

conclusionsTwo-phase designs have the potential to augment current M&E efforts in resource-limited settings by providing a framework for the collection and analysis of patient data. The design is cost-efficient in the sense that it often requires far fewer patients to be sampled when compared to standard designs.

Indexed as

AdolescentAdultAgedAnti-Retroviral AgentsCost-Benefit AnalysisDelivery of Health CareDisease OutbreaksFemaleHealth ResourcesHIV InfectionsHumansLogistic ModelsMalawiMaleMiddle AgedOutcome Assessment, Health CareAnti-Retroviral Agents

Identifiers

PMID25886976
PMCPMC4404107

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.